An artificial neural network for redundant robot inverse kinematics computation

A redundant manipulator can be defined as a manipulator that has more degrees of freedom than necessary to determine the position and orientation of the end effector. Such a manipulator has dexterity, flexibility, and the ability to maneuver in presence of obstacles. One important and necessary step in utilizing a redundant robot is to relate the joint coordinates of the manipulator with the position and orientation of the end-effector. This specification is termed as the direct kinematics problem and can be written as x = f(q) where x is a vector representing the position and orientation of the end-effector, q is the Joint vector, and f is a continuous non-linear function defined by the design of the manipulator. The inverse kinematics problem can be stated as: Given a position and orientation of the end-effector, determine the joint vector that specifies this position a q = f -1(x). and orientation. That is, For non-trivial designs, f -1 cannot be expressed analytically. This paper presents a solution to the inverse kinematics problem for a redundant robot based on multilayer feed-forward artificial neural network

Discrete Cosserat Approach for Multi-Section Soft Robots Dynamics

In spite of recent progress, soft robotics still suffers from a lack of unified modeling framework. Nowadays, the most adopted model for the design and control of soft robots is the piece-wise constant curvature model, with its consolidated benefits and drawbacks. In this work, an alternative model for multisection soft robots dynamics is presented based on a discrete Cosserat approach, which, not only takes into account shear and torsional deformations, essentials to cope with out-of-plane external loads, but also inherits the geometrical and mechanical properties of the continuous Cosserat model, making it the natural soft robotics counterpart of the traditional rigid robotics dynamics model. The soundness of the model is demonstrated through extensive simulation and experimental results for both plane and out-of-plane motions.Comment: 13 pages, 9 figure

Dynamic Active Constraints for Surgical Robots using Vector Field Inequalities

Robotic assistance allows surgeons to perform dexterous and tremor-free procedures, but robotic aid is still underrepresented in procedures with constrained workspaces, such as deep brain neurosurgery and endonasal surgery. In these procedures, surgeons have restricted vision to areas near the surgical tooltips, which increases the risk of unexpected collisions between the shafts of the instruments and their surroundings. In this work, our vector-field-inequalities method is extended to provide dynamic active-constraints to any number of robots and moving objects sharing the same workspace. The method is evaluated with experiments and simulations in which robot tools have to avoid collisions autonomously and in real-time, in a constrained endonasal surgical environment. Simulations show that with our method the combined trajectory error of two robotic systems is optimal. Experiments using a real robotic system show that the method can autonomously prevent collisions between the moving robots themselves and between the robots and the environment. Moreover, the framework is also successfully verified under teleoperation with tool-tissue interactions.Comment: Accepted on T-RO 2019, 19 Page

A general method for the numerical computation of manipulator singularity sets

The analysis of singularities is central to the development and control of a manipulator. However, existing methods for singularity set computation still concentrate on specific classes of manipulators. The absence of general methods able to perform such computation on a large class of manipulators is problematic because it hinders the analysis of unconventional manipulators and the development of new robot topologies. The purpose of this paper is to provide such a method for nonredundant mechanisms with algebraic lower pairs and designated input and output speeds. We formulate systems of equations that describe the whole singularity set and each one of the singularity types independently, and show how to compute the configurations in each type using a numerical technique based on linear relaxations. The method can be used to analyze manipulators with arbitrary geometry, and it isolates the singularities with the desired accuracy. We illustrate the formulation of the conditions and their numerical solution with examples, and use 3-D projections to visualize the complex partitions of the configuration space induced by the singularities.This work has been partially supported by the Spanish Ministry of Economy and Competitiveness under contract DPI2010-18449, and by a Juan de la Cierva contract supporting the fourth author.Peer Reviewe

A general method for the numerical computation of manipulator singularity sets

The analysis of singularities is central to the development and control of a manipulator. However, existing methods for singularity set computation still concentrate on specific classes of manipulators. The absence of general methods able to perform such computation on a large class of manipulators is problematic because it hinders the analysis of unconventional manipulators and the development of new robot topologies. The purpose of this paper is to provide such a method for nonredundant mechanisms with algebraic lower pairs and designated input and output speeds. We formulate systems of equations that describe the whole singularity set and each one of the singularity types independently, and show how to compute the configurations in each type using a numerical technique based on linear relaxations. The method can be used to analyze manipulators with arbitrary geometry, and it isolates the singularities with the desired accuracy. We illustrate the formulation of the conditions and their numerical solution with examples, and use 3-D projections to visualize the complex partitions of the configuration space induced by the singularities.Preprin

Control of Cooperating Mobile Manipulators

We describe a framework and control algorithms for coordinating multiple mobile robots with manipulators focusing on tasks that require grasping, manipulation and transporting large and possibly flexible objects without special purpose fixtures. Because each robot has an independent controller and is autonomous, the coordination and synergy are realized through sensing and communication. The robots can cooperatively transport objects and march in a tightly controlled formation, while also having the capability to navigate autonomously. We describe the key aspects of the overall hierarchy and the basic algorithms, with specific applications to our experimental testbed consisting of three robots. We describe results from many experiments that demonstrate the ability of the system to carry flexible boards and large boxes as well as the system’s robustness to alignment and odometry errors

Control of Cooperating Mobile Manipulators

We describe a framework and control algorithms for coordinating multiple mobile robots with manipulators focusing on tasks that require grasping, manipulation and transporting large and possibly flexible objects without special purpose fixtures. Because each robot has an independent controller and is autonomous, the coordination and synergy are realized through sensing and communication. The robots can cooperatively transport objects and march in a tightly controlled formation, while also having the capability to navigate autonomously. We describe the key aspects of the overall hierarchy and the basic algorithms, with specific applications to our experimental testbed consisting of three robots. We describe results from many experiments that demonstrate the ability of the system to carry flexible boards and large boxes as well as the system’s robustness to alignment and odometry errors

Parallel Manipulators

In recent years, parallel kinematics mechanisms have attracted a lot of attention from the academic and industrial communities due to potential applications not only as robot manipulators but also as machine tools. Generally, the criteria used to compare the performance of traditional serial robots and parallel robots are the workspace, the ratio between the payload and the robot mass, accuracy, and dynamic behaviour. In addition to the reduced coupling effect between joints, parallel robots bring the benefits of much higher payload-robot mass ratios, superior accuracy and greater stiffness; qualities which lead to better dynamic performance. The main drawback with parallel robots is the relatively small workspace. A great deal of research on parallel robots has been carried out worldwide, and a large number of parallel mechanism systems have been built for various applications, such as remote handling, machine tools, medical robots, simulators, micro-robots, and humanoid robots. This book opens a window to exceptional research and development work on parallel mechanisms contributed by authors from around the world. Through this window the reader can get a good view of current parallel robot research and applications

Practical identifiability of the manipulator link stiffness parameters

International audienceThe paper addresses a problem of the manipulator stiffness modeling, which is extremely important for the precise manufacturing of contemporary aeronautic materials where the machining force causes significant compliance errors in the robot end-effector position. The main contributions are in the area of the elastostatic parameters identification. Particular attention is paid to the practical identifiability of the model parameters, which completely differs from the theoretical one that relies on the rank of the observation matrix only, without taking into account essential differences in the model parameter magnitudes and the measurement noise impact. This problem is relatively new in robotics and essentially differs from that arising in geometrical calibration. To solve the problem, several physical and statistical model reduction methods are proposed. They are based on the stiffness matrix sparseness taking into account the physical properties of the manipulator elements and also on the heuristic selection of the practically non-identifiable parameters that employs numerical analyses of the parameter estimates. The advantages of the developed approach are illustrated by an application example that deals with the stiffness modeling of an industrial robot used in aerospace industry